Access the Eastern Wind Integration Data Set Resources

Methodology

The Eastern Wind Integration Data Set consists of 3 years (2004–2006) of 10-minute
wind speed and plant output values for 1,326 simulated wind power plants as well
as next-day, 6-hour, and 4-hour forecasts for each plant. AWS Truepower created the
data set with oversight and assistance from NREL.

After testing various mesoscale models, AWS Truepower settled on the MASS v.6.8
model to generate the wind data for the Eastern Wind Integration and Transmission Study. The model is initialized with input from the National Centers for Environmental
Prediction/National Center for Atmospheric Research Global Reanalysis data set and
assimilates both surface and rawindsonde data. The model used a nested grid scheme,
with the final output resolution of 2 kilometers (km).

Wind power plant locations were determined using a proprietary AWS Truepower wind
speed map of the study area along with 10 years of speed distributions previously
computed by AWS Truepower. The wind resource at each cell was computed by combining
these data sets with a composite turbine power curve. Wind power plants were then
created by combining cells with close proximity and similar wind characteristics
(subject to environmental, topographic, and other exclusions). Size and state-by-state
distribution of wind power plants were controlled to give a diverse selection of
plants. (For example, it was necessary to reduce the minimum capacity factor threshold
to get enough plants in Connecticut, Rhode Island, New Jersey, and Delaware.)

The wind speed and power output time series for each wind power plant were computed
by combining the mesoscale grid output with the composite turbine power curves, the
list of cells contained in each plant, and other data. Adjustments were made for
model biases, wake losses, the impact of gusts, availability, and other factors.

For a description of the overall project and more information about the modeling and
inputs, read AWS Truepower's final report .

Site Selection

Land-based sites are actually simulated wind power plants composed of many nearby
grid points that have similar wind characteristics. Sites range from 5 km2 to 160 km2, and maximum power output ranges from 100 megawatts (MW) to 1,435 MW. (Data from
the individual grid points and the shape and layout of the sites are not available.)
The site screening process excluded areas of open water, wetlands, parks, steep slopes,
and nonpublic federal land. Airports and developed areas, along with buffer zones
surrounding them, were also excluded.

The final site list contains 1,326 sites totaling 580 gigawatts (GW). The bulk of
the sites fall between 100 MW and 600 MW. A smaller number (150) of "megasites" with
rated capacities exceeding 1,000 MW were also chosen. All of these are in the Great
Plains. A separate screening with a lower capacity factor threshold was performed
for Connecticut, Rhode Island, New Jersey, and Delaware, with 30 sites selected in
these states.

Offshore sites were chosen from a 2-km grid, wherein each grid point represented 20
MW of offshore wind capacity. Selected grid points were at least 8 km from shore and
in water no deeper than 30 meters. A total of 4,948 sites in the Atlantic Ocean and
four of the five Great Lakes were selected.

Wind Power Plant Output

Wind power plant output time-series values were computed by summing the contributions
of each grid cell in the site. Three composite power curves (computed by averaging
two or three power curves from commercial turbines) were available, and the choice
of power curve was based on the average wind speed at the site. Adjustments were made
for model biases, wake losses, wind gusts, turbine and plant availability, and other
factors.

Forecasts

AWS Truepower produced hourly forecasts for three time horizons: next-day, 6-hour,
and 4-hour. Each set of forecasts was synthesized by running a statistical forecast
synthesis tool written by AWS Truepower called SynForecast. This tool uses actual
forecasts and observed plant output to develop a set of transition probabilities that
are then applied stepping forward in time from a random starting point in a process
known as a Markov chain.

As part of the wind data synthesis procedure, observed data were assimilated into
the weather simulation at 12-hour intervals, which caused the data discontinuity.
The problem was identified during the Eastern Wind Integration and Transmission Study
and partially fixed. The discontinuity was not significant in individual wind power
plant profiles; however, it was more prominent in aggregations of wind power plant
profiles. Because much of the statistical analysis in the Eastern Renewable Generation
Integration Study will be performed on aggregations, it was necessary to develop
and implement a fix.

Although the primary goal of the update was to mitigate the 12-hour discontinuity
in aggregate profiles, the wind power conversion was also updated to better reflect
future wind turbine technology. The 12-hour discontinuity was addressed by a technique
that adjusted the correlated component of the wind power fluctuations by adding a
proportion of the adjustment to each individual site. It was applied on a state-by-state
basis. The updated wind power conversion incorporated new composite power curves
that use larger wind turbines.

The wind power hourly forecasts were also updated based on the new synthesized 10-minute
wind power profiles. In general, the same methodology was used to generate these
forecasts as was used in the original Eastern Wind Integration and Transmission Study
wind database.